Applying weights to Randomized Arrays In a Dataframe

Specific Domains Statistics
1

Hello Everyone:

Is there a way to apply weights to arrays in
a data such as:

DF = DataFrame(Id = 1:10, Tablets = (rand(1:02:50),10), Desktops =(rand(1:02:50),10), Mobiles = (rand(1:01:50), 10))

If I wanted to apply a 0.4, 0.5, 0.1 proportion to Tablets, Desktops, and Mobiles, How would I approach this? I am seeing, SimpleRandom.jl? I am seeing this package applies the probabilities via report(), but is there a way the probabilities can be applied to the data in the DataFrame?

Thanks.

2

DF is a 10-row dataframe and your question does not make sense to me. Actually, not relevant to DataFrames but try to use StatsBase.sample.

sample(["Tablets", "Desktops", "Mobiles"], Weights([0.4,0.5,0.1]))

Example:

using StatsBase
items = 0:5
weights = 0:5
sample(items, Weights(weights))

julia> my_samps = sample(items, Weights(weights), 10)
10-element Array{Int64,1}:
 4
 3
 2
 1
 3
 3
 5
 5
 2
 2